National Academies Press: OpenBook

A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials (2012)

Chapter: 4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks

« Previous: 3 Critical Questions for Understanding Human and Environmental Effects of Engineered Nanomaterials
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 107
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 108
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 109
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 110
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 111
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 112
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 113
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 114
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 115
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 116
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 117
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 118
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 119
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 120
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 121
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 122
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 123
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 124
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 125
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 126
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 127
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 128
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 129
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 130
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 131
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 132
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 133
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 134
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 135
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 136
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 137
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 138
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 139
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 140
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 141
Suggested Citation:"4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks." National Research Council. 2012. A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials. Washington, DC: The National Academies Press. doi: 10.17226/13347.
×
Page 142

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

4 New Tools and Approaches for Identifying Properties of Engineered Nanomaterials That Indicate Risks This chapter articulates needs for tool development for exploring how properties of engineered nanomaterials (ENMs) influence critical biologic and environmental interactions (see Figure 2-1). The research needs are directed at the gaps in evidence presented in Chapter 3 and are based on the conceptual framework for assessing risks described in Chapter 2. The primary needs are access to nanomaterials for hypothesis-testing and for assessing exposure to and effects of ENMs; methods for characterizing materials, including methods for detecting, quantifying, and characterizing ENMs in environmental and biologic samples; exposure and toxicity-testing methods and reporting stan- dards; exposure and effects modeling; and informatics for developing compre- hensive predictive models of exposure, hazards, and risk. Informatics is de- fined here as the infrastructure and information science and technology needed to integrate data, information, and knowledge on the environmental, health, and safety (EHS) aspects of nanotechnology. An overall purpose of informat- ics in this context is to organize data so that they can be mined to determine how nanomaterial properties affect their exposure and hazard potential and to estimate overall risks to the environment and human health. (The research needs presented here are summarized according to categories of tools at the end of this chapter, Table 4-1.) CHARACTERIZED NANOMATERIALS FOR NANOTECHNOLOGY- RELATED ENVIRONMENTAL, HEALTH, AND SAFETY RESEARCH Identifying ENM properties that influence biologic and environmental in- teractions will require well-characterized libraries of materials for hypothesis- testing and reference or standard test materials that may be used as benchmarks for comparison among studies, to validate protocols or measurements, or to test 107

108 Identifying Properties of Engineered Nanomaterials That Indicate Risks specific hypotheses related to material properties and specific outcomes (for example, mobility in the environment or toxic responses). The lack of wide- spread access to such materials and the lack of agreement as to which materials to consider as standards slows progress toward linking properties of ENMs with their effects, makes comparisons among studies difficult, and limits the utility of data collected for informatics (see section “Barriers to Informatics”). To characterize correlations between nanomaterial properties and the key interactions or end points in humans and the environment, several tools are needed, including adequately characterized materials that have different proper- ties, appropriate assays for examining interactions or end points, and experimen- tal data of sufficient breadth and depth for assessing correlations between nano- material properties and the behavior of the materials. Materials needed for developing those correlations are in four general categories, which are described below. Each type must be characterized sufficiently for test results to be repro- ducible and for correlations between observed effects and material structure and composition to be established and ultimately used to predict effects of new ma- terials on the basis of knowledge of their structure and composition. Research or Commercial Samples These samples may be available from R&D teams or from materials that are near commercialization or in commerce. Many EHS studies have been con- ducted with such materials because of their availability and because people or the environment may be exposed to these materials. The material definition and characterization metrics needed for nanomaterial research and commercial use are typically different from those needed to study material-effect correlations, and the former materials often do not have the definition, purity, or characteriza- tion needed for research purposes. It is important to study the biologic and eco- logic effects of the commercial materials, as such materials (and their impuri- ties) have the greatest potential compared to other types of materials to be released into the environment (Alvarez et al. 2009; Gottschalk and Nowack 2011). However, there are limitations to the use of commercial materials in the development of predictive models. The materials are generally insufficiently characterized; when they are studied in isolation, the polydispersity and lot-to- lot variation in their properties make them unsuitable for developing data that can be used for prediction. For greater utility in prediction, material characteri- zation that is specific to EHS research should be conducted in addition to that carried out by material researchers or producers (Bouwmeester et al. 2011). Reference Materials Reference materials are developed for hypothesis-driven research or for use as benchmarks to compare results among various tests or assays or among laboratories. They are designed and characterized so that material characteristics

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 109 can be linked to biologic-nanotechnologic or ecologic-nanotechnologic interac- tions or end points. Reference materials are often highly purified to reduce or eliminate the effects of impurities on responses (Oostingh et al. 2011). They may not attain the same level of scrutiny as standards (see discussion below), but they require a smaller investment of time and resources to develop. Sources of these materials include academic and government research laboratories (Na- tional Institute of Standards and Technology), commercial suppliers (for exam- ple, nanoComposix, Nanoprobes, Inc., and Strem Chemicals, Inc.), and interna- tional harmonization efforts (such as the Organisation for Economic Co- operation and Development and the International Alliance for NanoEHS Har- monization). Standard or reference materials can be used to compare test or measurement results among laboratories or to compare the results from different tests or measurements. However, because these materials typically represent specific, narrow structural types that are not easily manipulated to access a broad range of structural features, it is difficult to develop more general design rules from studies of these materials. Libraries Libraries are collections of reference materials in which structural or com- positional variables are systematically varied throughout a series of members of the library. For example, the nanoparticle core material and size might be kept constant while a surface coating varies in its external charge—positively, nega- tively, or not at all. Libraries allow the influence of nanomaterial structure and composition on biologic or ecologic effects to be explored so that quantitative structure-activity relationships can be determined. Libraries also facilitate explo- ration of hypotheses related to material-effect correlations. To serve that pur- pose, libraries should be appropriately defined and characterized as described above for reference materials. Ideally, the materials in libraries have sufficient range and granularity across the structural or compositional measures of interest. Given the importance of detailed characterization for establishing cause-effect correlations, characterization data on each sample lot need to be provided with each sample. Standards Standards are samples that have been thoroughly tested to support labora- tory comparisons or to calibrate and harmonize measurements conducted in dif- ferent laboratories. They typically are prepared and provided for by standard- setting organizations or agencies (for example, the National Institute of Stan- dards and Technology). The benefits of developing standard materials that meet the criteria for definition and characterization are clear; however, the time (years) and expense of developing such standards sometimes restrict their use in EHS studies.

110 Identifying Properties of Engineered Nanomaterials That Indicate Risks Research Needs for Providing Well-Characterized Nanomaterials for Nanotechnology-Related Environmental, Health, and Safety Research  Development of characterized, reproducible, but not necessarily uni- form, “real-world” materials for testing.  Development of libraries of uniform, well-characterized reference ma- terials of varied size, shape, aspect ratio, surface charge, and surface function- ality.  Development of standard materials for calibrating various assays and measurement tools.  Development of new synthetic methods and postsynthesis separation and purification methods for accessing the different types of materials, reducing polydispersity, and decreasing lot-to-lot variability and for efficiently removing undesirable impurities from nanomaterials without causing their decomposition or agglomeration. TOOLS, STANDARDIZED CHARACTERIZATION METHODS, AND NOMENCLATURE OF ENGINEERED NANOMATERIALS Protocols for Measuring and Reporting a Minimum Set of Material Properties for Pristine Engineered Nanomaterials Used in Nanotechnology-Related Environmental, Health, and Safety Research With regard to characterization of research and commercial samples for EHS testing, there is a need for systematic approaches for adequately and sys- tematically defining the structure, composition (including surface chemistry), and purity of samples so that data reported through the nanotechnology-related EHS research community ultimately can be used to correlate structure and com- position of nanomaterials with their behaviors and effects. Most of the tools needed to accomplish that goal are available for pristine1 starting materials (Has- sellöv et al. 2008). One exception is the lack of tools for characterizing the de- tails of the surface chemistry of nanoparticles, including defects in surface lay- ers, mixtures of bound molecules, and conformation of the adsorbed layer of organic macromolecules of high molecular weight. That type of characterization should form the basis of a working definition (or nomenclature) for the material. For example, the intent would be to move from labeling a material as “gold nanoparticles” to the more specific designation of “mercaptopropionic acid sta- bilized 1.5  0.4 nm gold nanoparticles.” Each material lot needs to be charac- terized in that way (because of variations from batch to batch). Polydisperse and impure samples (for example, materials that have varied chemical composition 1 Pristine refers to the nanomaterial as manufactured, before any alterations in the environment.

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 111 or that contain endotoxins) are inherently more complicated to characterize be- cause they are mixtures. For commercial or research samples, a material should be characterized to assess purity and size distribution in the state in which it is provided to researchers. Reference materials and libraries may require extensive purification to remove impurities or to decrease polydispersity that complicates data interpretation and characterization. Despite concerted efforts to establish a minimum set of standard properties to define ENMs, there is still lack of agreement in the research community as to what constitutes this minimum set of properties. Yet there has been some pro- gress in demonstrating that there is overlap in their nanomaterial properties (MINChar Initiative 2009; Boverhof and David 2010). Without agreement on the properties and how they can be communicated, with full participation of the nanomaterial-EHS research community, it will not be possible to define the starting materials for nanomaterial-EHS research adequately or to create “classes” of ENMs that have similar surface chemistries and behaviors. There- fore efforts to compare results among studies with informatics or other ap- proaches will be hindered (see section “Barriers to Informatics”). Ultimately, a classification of ENMs will probably be needed for regulatory purposes, but the criteria for what constitutes a “class” have not been determined. Because of the complexity of nanomaterial structures and compositions, a wide array of techniques is typically needed to characterize each new nanomate- rial adequately. Each technique provides a partial definition of the material. For example, for a ligand-stabilized inorganic nanoparticle, transmission electron microscopy (TEM) and small-angle x-ray scattering can be used to define nanoparticle cores (von der Kammer et al. 2012); x-ray photoelectron spectros- copy and Fourier-transform infrared (FTIR) spectroscopy define surface chemis- try; atomic-force microscopy provides information about the overall dimension of the core plus shell; thermal gravimetric analysis provides the ratio of ligand mass to core mass; and solution methods, such as nuclear magnetic resonance spectrometry, can be used to detect small-molecule impurities. Because such exhaustive characterization of each nanomaterial sample is expensive and time- consuming, minimal characterization sets have been proposed (for example, Boverhof and David 2010). One approach is to make the same comprehensive or subset of measurements for every material; however, this approach can lead to unneeded measurements of some materials or insufficient characterization of others. Other approaches seek to determine the minimum material properties that need to be defined to describe materials used in nanotechnology-related EHS studies adequately and should address at least physical dimensions, com- position (including surface chemistry), and purity (MINChar Initiative 2009; Richman and Hutchison 2009). From these approaches key material descriptors should emerge that will facilitate attribution of material effects, data-sharing, and comparison of properties and effects between samples. In addition to assessment of pristine material samples and dry powders, analytic methods should include characterization of ENMs in various reference

112 Identifying Properties of Engineered Nanomaterials That Indicate Risks suspension media that reflect real-world fluid suspension media and concentra- tions (for example, water, phosphate-buffered solution, lung fluid, and plasma) because ENM properties are determined in part by the dispersing fluid and ENM concentration (Oberdörster et al. 2005). Reactivity measurements are also needed and could include redox activity and reactive-oxygen species generation. Protocols and methods will need to be specific to a nanomaterial’s charac- teristics, including particle type, size, shape, coating type, and media type, be- cause not all methods will be applicable to all types of ENMs. There are some key issues that if left unaddressed lead to problems, including methods for dis- persing nanoparticles in media, protocols for reproducibly preparing samples for analysis and investigation, and approaches to using multiple instruments to cross-check and confirm results from techniques that may provide only partial answers. There is a need for widely accepted protocols for sample preparation and measurements; for example, see the National Cancer Institute Nanotechnol- ogy Characterization Laboratory’s effort to develop and publish assay cascade protocols (including NIST/NCL 2010). The sensitivity of the protocols to the array of variables that may affect their outcome (for example, solution pH and energy input for creating a dispersion) should be determined and reported as part of the protocols. Tools and methods are needed to characterize the surface properties of ENMs better in situ or in vivo. As discussed in Chapter 3, these properties will depend on the media in which they are dispersed so methods should be tailored to the exposure conditions. The surface properties of ENMs will determine their interactions with environmental and biologic media. Many tools are available to characterize size, elemental composition, and structure, but fewer are capable of characterizing only the surfaces of ENMs. Surface curvature, roughness, crystal faces, and defects may all affect the physical, chemical, and toxicologic proper- ties of an ENM; it is not possible to characterize those features adequately with existing microscopic and spectroscopic techniques (for example, electron spec- troscopy for chemical analysis, TEM, and FTIR). Surface functional groups— such as adsorbed or grafted surfactants, polymers, polyelectrolytes, proteins, and natural organic matter (NOM)—can prevent or enhance agglomeration and deposition (Phenrat et al. 2008; Saleh et al. 2008; Jarvie et al. 2009), toxicity (Gao et al. 2005; Nel et al. 2009; Phenrat et al. 2009), and bioavailability (Kreuter 1991). Despite the influence of bound coatings on ENM behavior, methods for readily measuring the distribution and, more important, the confor- mation of the bound species on the surface of ENMs are not widely available. Cryoelectron microscopy combined with computational methods can provide information on conformation of antibodies or other molecules, but these meth- ods are time-consuming, and results can be influenced by sample-preparation methods. Methods for measuring those features in vivo, in vitro, or in situ do not exist and their development is necessary to begin to correlate the in situ proper- ties of ENMs with their behavior and effects.

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 113 Research Needs for Developing Protocols for Measuring and Reporting a Minimum Set of Material Properties for Pristine Engineered Nanomaterials Used in Nanotechnology-Related Environmental, Health, and Safety Research  Identify agreed-on minimum characterization principles to develop standardized descriptors for ENMs related to the key physical characteristics of the materials that can be used to describe materials for data-reporting and in- formatics and for cross-referencing nomenclatures (that is, nanomaterial vo- cabularies and ontologies).  Determine best practices for characterizing groups of particle types (for example, by chemical composition or chemical-surface reactivity, for spe- cific size ranges, for specific coating types or structures, and in relevant suspen- sion media), including those to characterize reactive surface area, nanometer and subnanometer surface features of ENMs, and adsorbed molecules and mac- romolecules on ENMs.  Develop standard reactivity measures and protocols for ENMs, includ- ing a standardized approach for measuring the sensitivity of methods to impor- tant variables (for example, pH, ionic strength, organic matter, and biomacro- molecules). Detection and Characterization of Nanomaterials in Complex Biologic and Environmental Samples Chemical and physical information on ENMs in environmental and bio- logic matrices is needed. Many existing analytic techniques from material sci- ence and other disciplines are applicable to ENMs, but their use in measuring and characterizing low concentrations and heterogeneous matrices will require additional development or in some cases, development of completely new ap- proaches. A recent review by von der Kammer et al. (2012) summarizes many of the analytic tools and research needs for detecting and characterizing ENMs in environmental and biologic matrices. There are few analytic tools that can be used to quantify and characterize ENMs in situ (for example, in air, soil, or sediment samples), in vitro (for exam- ple, in cells or tissues), or in vivo at the low concentrations expected for most nanomaterials (in the low parts-per-billion to low parts-per-trillion range) (Has- sellöv et al. 2008; Gottschalk et al. 2009; Tiede et al. 2009; von der Kammer et al. 2012). Some examples include radiolabeled materials (Hong et al. 2009; Gib- son et al. 2011; Peterson et al. 2008); fluorescence (Schierz et al. 2010); mass spectrometry (MS) and single particle MS techniques (von der Kammer et al. 2012); spatially resolved X-ray analyses (von der Kammer 2012); and differen- tial mobility analysis (Morawska et al. 2009), a well developed technique used to quantify the number and size distribution of nanoparticles in air.

114 Identifying Properties of Engineered Nanomaterials That Indicate Risks Because of the lack of analytic tools, relationships between properties of materials measured ex situ (for example, nanoparticle size by TEM) and their in situ or in vivo behaviors need to be inferred, and this limits our understanding of how ENMs may be affected by such processes as in situ and in vivo transforma- tions, biodistribution, and distribution in environmental samples. Tools for quantifying and characterizing ENMs in the environment or in organisms typically have either a broad or a narrow spectrum. Broad-spectrum tools are applicable to a variety of sample types but require relatively high con- centrations of materials (for example, non-spatially resolved synchrotron x-ray spectroscopy methods) and most often require removal from media to conditions that are not representative of in vivo or in situ environments (for example, mi- croscopy). Narrow-spectrum tools are highly specific to a material (for example, near-infrared detection of single-walled carbon nanotubes (Leeuw et al. 2007) that can be detected at low material concentrations and potentially under in situ or in vivo conditions, but modification of the material may limit sensitivity. These narrow-spectrum tools must be developed at great expense for each type of nanomaterial. The variety of ENMs that need to be studied makes use of nar- row-spectrum tools expensive and perhaps intractable. Detection in vivo or in situ can be difficult because of the low concentrations of materials released into an organism or the environment. Even if the material has not been transformed, detection is difficult; if it has been transformed, detection is even more difficult. Strategies and tools for detecting and tracking materials are needed. These strategies should include combinations of techniques to detect and characterize ENMs in complex matrices, and to differentiate between naturally occurring ENMs and naturally occurring nanomaterials (von der Kammer 2012). Fluorescence is a common strategy that is used to localize materials, but more general techniques are needed for materials that are not fluorescent or for situations in which incorporation of a fluorescent tag interferes with the proc- esses being investigated by modifying the material’s surface properties. Another approach that will benefit nanotechnology-related EHS research is to label (for example, radiolabels) and track surface functional groups (coatings) that are being used on ENMs; however, care must be taken to ensure that the functional groups are not readily removed from the ENM by chemical or biologic reac- tions. Labeling approaches will need to be coupled with sensitive high- resolution methods to characterize the interactions between ENMs and the me- dium at the site of distribution and localization. Tracking ENMs in vivo or in situ could advance research in the field considerably, but simply tracking the presence of ENMs in these systems is not sufficient to correlate their properties with their behaviors. Methods also are needed to characterize the surface proper- ties of ENMs in situ. Quantifying the number and distribution of particle sizes in air samples us- ing differential mobility analyzers (DMAs) is a well established technique (Ehara and Sakurai 2010). A DMA can quantify number concentration and size distributions, but used in isolation, it cannot determine chemical composition or surface area concentration. Further, it cannot distinguish between airborne

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 115 ENMs and naturally occurring or incidental nanomaterials. However, a DMA coupled with a single aerosol mass spectrometer can provide chemical speci- ation of airborne particles, and potentially can distinguish between ENMs and naturally occurring nanoparticles if the naturally occurring nanoparticles have a consistent chemical composition that is distinct from that of naturally occurring nanomaterials (Smith et al. 2010; Zhao et al. 2010). Because of the likelihood of human exposure to nanomaterials in manufacturing environments, further de- velopment of instrumentation that measures chemical composition, aggregation state, and distinguishes ENMs from naturally occurring nanomaterials in air samples is needed (for example, Zhao et al. 2010; Bzdek et al. 2011). As discussed in Chapter 3, ENMs will be transformed in the environment (for example, by aggregation, oxidation, sulfidation, or adsorption of macro- molecules). These transformations will affect distribution of ENMs in the envi- ronment or an organism. These modifications may also make their detection difficult (von der Kammer et al. 2012). Methods and tools are needed for assess- ing the transformation of ENMs in situ (for example, in soils, sediments, or treatment-plant effluent), in vitro (for example, in cells or tissue), and in vivo (for example, in rats). Research Needs for Detection and Characterization of Nanomaterials in Complex Biologic and Environmental Samples  Develop model ENMs that can be tracked without introduction of ex- perimental artifacts in exposure and toxicity studies.  Develop analytic tools and processes that can detect ENMs at low (relevant) concentrations in situ or in vivo, followed by tools to track and char- acterize ENM properties (for example, reactivity, reactive surface area, nano- meter and subnanometer surface features, aggregation-agglomeration, and ad- sorption of organic macromolecules) in situ or in vivo.  Develop tools and processes to assess the rate and degree of transfor- mation of ENMs in vivo or in situ, especially alteration of surface properties of ENMs due to adsorption of proteins and lipids (corona formation) and NOM. STANDARDIZED EXPERIMENTAL PROTOCOLS FOR NANOTECHNOLOGY-RELATED ENVIRONMENTAL, HEALTH, AND SAFETY RESEARCH Development of New Protocols or Modification of Existing Protocols for Toxicity Testing and Determination of Population and Ecosystem Effects A focused, coordinated research effort is needed to identify and validate existing or newly developed toxicity-testing protocols and best practices, such as dosimetrics (Teeguarden et al. 2007), for an agreed-on set of toxicity end points for ENMs (NRC 2007). The protocols would include rigorous physicochemical characterization of particle types, use of relevant cell types or cell systems (for

116 Identifying Properties of Engineered Nanomaterials That Indicate Risks example, air-liquid interface) to simulate relevant in vivo exposures, relevant dose-response protocols, relevant time-course protocols, and assessments of biomarkers, such as inflammatory end points, that have relevance to in vivo pathway models (for example, sustained inflammation). For ecologic-health research, a set of sensitive species will need to be identified in the risk- characterization phase. Development of ecologic and human-health test methods should also include coordinated interlaboratory testing validation for existing toxicity tests and end points and appropriate doses and dosing protocols in the case of newly developed tests and end points. The appropriate end points for toxicity tests need to be determined. They should be determined from in vivo model pathways that are identified after inha- lation, ingestion, or dermal exposure to ENMs. The end points for measurement after pulmonary exposure could include the following: reactive oxidant species; inflammatory biomarkers; cytotoxicity end points; cell proliferation, fibrosis, and hyperplastic responses; and histopathology, particularly for time points after exposure. For environmental health, validation of standard measures of alterna- tive (non-acute) end points of exposure to ENMs (for example, growth, repro- duction, behavior, or stress) should be determined. Additional data are needed from assay systems that have sublethal outcomes and on more types of nanoma- terials to develop testing methods that are simple but have predictive value for hazard identification (Ankley et al. 2010). To develop simple non-in vivo assays that will eventually allow high- throughput testing and provide results that predict in vivo effects (hazard identi- fication), correlations need to be explored between the end points measured in vitro and the expected effects in vivo. That will require standardized and vali- dated in vitro methods (for example, standardized cell types and exposure proto- cols) that represent specific, realistic exposures (including the materials used and the exposure routes), and doses and validation against results of in vivo studies. This is a critical step in realizing the benefits of high-throughput screen- ing strategies proposed for ENMs. Development of appropriate in vitro assays that can predict in vivo re- sponses requires a detailed understanding of biodistribution of ENMs and the mechanistic pathways by which ENMs exert a toxic effect on a specific organ. Research is needed to elucidate those toxicity mechanisms for representative or- ganisms, considering appropriate dosimetry (see above) and well-characterized ENMs, so that ENM properties can be correlated with mechanisms of injury. Genomic tools may generate important hypotheses regarding toxicity mechanisms and may be useful for grouping nanomaterials by expected re- sponse on the basis of their properties, as has been observed in several studies with well-characterized chemicals (Bartosiewicz et al. 2001a,b; Hamadeh et al. 2002; Klaper and Thomas 2004; Dondero et al. 2011). However, in vivo data are needed to validate the genomic data with organism responses. Although genom- ics tools are available, research is needed to determine how much and what type of gene or protein expression changes will result in long-term effects of ENM

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 117 exposures. Gene and protein expression measured in vitro with these tools must be correlated with measured effects in vivo. The protocols for assessing ecotoxicity include those for assessing human toxicity but should also include protocols for predicting sensitive species and effects on communities and ecosystems if they are to be useful for risk assess- ment (Ankley et al. 2010). Those include effects on interactions among species, species community assemblages, biodiversity, and ecosystem function. There is no suite of standard tests for assessing community and ecosystem effects of chronic exposure to ENMs. That limitation is not peculiar to ENMs and presents a serious challenge to the modeling of ecologic effects. Research Needs for Development of New Protocols or Modification of Existing Protocols for Toxicity Testing  Develop new standard toxicity-testing protocols or modify existing pro- tocols for ENMs to include relevant cell types and organisms, appropriate do- simetrics, and appropriate toxicity end points (for example, chronic-toxicity end points) and validate those protocols.  Identify and validate toxicity-pathway models and mechanisms to cor- relate in vitro end points with in vivo responses.  Improve the interpretability of genomic tools by determining how gene expression and protein expression are related to ENM toxicity and mechanisms. Research Needs for Development of New Protocols or Modification of Existing Protocols for Determination of Population and Ecosystem Effects  Develop and validate a suite of standard tests that can indicate the po- tential for population or ecosystem effects of chronic ENM exposure on specific organisms.  Develop methods for understanding ecosystem effects (that is, effects on systems of systems) that result from indirect effects of nanomaterials, such as carbon and nitrogen cycling. Development of New Protocols or Modification of Existing Protocols for Exposure Assessment Exposure assessment and modeling (discussed later) will require informa- tion about sources, transport, transformations, persistence, and bioavailability of ENMs released into the environment (Johnston et al. 2010). Standard testing protocols need to be conducted to determine the properties that influence trans- port, transformation, persistence, and bioavailability. The protocols need to be assessed and validated with a variety of ENM types and classes and under an array of environmental conditions (for example, freshwater, seawater, terrestrial, and groundwater environments). Although it is desirable for the protocols to be

118 Identifying Properties of Engineered Nanomaterials That Indicate Risks applicable to a wide variety of ENMs that have differing properties and to vari- ous environmental conditions, it may not be practical, given the different envi- ronmental conditions that must be considered. Ideally, the protocols would be readily adaptable to new material properties as they are introduced. Environmental transport will be affected by attachment of ENMs to them- selves (aggregation and agglomeration) or to inorganic minerals, organic carbon, or organisms (for example, bacteria or plant roots). A variety of methods are available to measure attachment of ENMs to surfaces in the environment, in- cluding studies of column deposition and analyses using quartz crystal micro- balance (Saleh et al. 2008; Petosa et al. 2010). Because of the array of variables influencing attachment of nanomaterials to environmental surfaces including physical characteristics of the nanomaterial, the properties of the environmental surface, and solution conditions, it is extremely difficult to compare attachment coefficients reported in the literature for different nanomaterials and surfaces. Standardized protocols for measuring and reporting the attachment coefficients should be developed so that the many studies of ENM attachment to environ- mental surfaces can be used to correlate the properties of ENMs with their pro- pensity to attach to environmental and biologic surfaces. ENMs released into the environment undergo a variety of transformations depending on the environmental conditions (for example, redox state, presence of NOM, or available sulfide) or biologic conditions (for example, biologic fluid and cell type) (Wiesner at al. 2006; Metz et al. 2009; Bottero and Wiesner 2010). A few types of transformations are likely to have the greatest influence on exposure potential—for example, aggregation, dissolution, adsorption of NOM or biomacromolecules, sulfidation, photodegradation, and biodegradation. Standard protocols need to be developed to “weather” or “age” ENMs in envi- ronmental and biologic media and to determine the rate and extent of transfor- mation expected as a function of environmental and ENM properties. The aging procedures should consider expected transformations for ENMs, including dis- solution, sulfidation, oxidation-reduction, adsorption of organic matter and bio- macromolecules, biodegradation, and photodegradation. Relevant environmental media that should be considered include wastewater-treatment plant biosolids, terrestrial environments in which biosolids are used as fertilizer, sediment, and physiologic buffers. The most stable or metastable forms of the transformed materials and the persistence of the transformed materials should be determined. Protocols for characterizing and reporting the properties and persistence of transformed ENMs should be established to permit comparisons among studies. Many transformations of ENMs will not produce a thermodynamic equi- librium with their surroundings, including such adsorbed macromolecules as proteins and higher-molecular-weight polymeric coatings (Casals et al. 2010), because these transformations are kinetically controlled and path-dependent. A better understanding of the kinetics of ENM transformations is needed, espe- cially understanding of the rates of displacement of adsorbed macromolecules, for example, proteins displacing a polyethylene glycol coating on an ENM or

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 119 various proteins displacing each other in plasma (Lynch et al. 2007; Walczyk et al. 2010; Monopoli et al. 2011). ENMs may be present in environmental media at very low concentrations, so acute toxicity will not be a primary concern. However, organisms may be exposed to ENMs at low concentrations for long periods. Thus, the bioavailabil- ity of ENMs and potential long-term ecologic effects need investigation. Many factors may influence bioavailability of ENMs, including environmental condi- tions, physical and chemical properties of transformed ENMs, exposure routes, and timing of exposure during an organism’s lifespan. Protocols are needed to assess the bioavailability of ENMs in a variety of exposure scenarios and at real- istic exposure concentrations. Initially, these protocols should be developed for an agreed-on suite of indicator organisms and soil, sediment, and water-column exposures. Other organisms can be added as needed. Standard protocols and analytic methods that measure number, surface area, and mass concentration are also needed to assess direct human exposures to ENMs via inhalation. For example, measurements from traditional mass- based exposure assessment, such as PM2.5, are not necessarily correlated with nanoparticle number concentrations (Jeong et al. 2004). There are two distinct needs. First, personal exposure monitors are needed to collect data for occupa- tional and epidemiology studies. Second, exposure assessment methods that are easier to operate and that can be used to support regulatory decision-making should be developed. Research Needs for Development of New Protocols or Modification of Existing Protocols for Exposure Assessment  Develop and validate standard protocols for measuring and reporting attachment of ENMs to biologic and environmental surfaces.  Establish protocols that can be applied to pristine ENMs to identify and classify their stability in the environment. Develop protocols to provide “weathered,” transformed materials for study (for example, in transport and toxicity studies).  Develop and validate protocols to assess bioavailability of ENMs to specific indicator organisms identified in a site-specific risk-assessment model.  Develop standard protocols and analytic methods that measure num- ber, surface area, and mass concentration to assess human inhalation exposures to ENMs. EXPOSURE MODELING The variety of ENM types and properties necessitates the development and use of models to predict exposure to ENMs and the effects of exposure. This will include models of exposure assessment, bioavailability, mechanistic toxic- ity, biodistribution, and dosimetry. Proper problem formulation (see Chapter 2) is essential for the successful design and application of the models.

120 Identifying Properties of Engineered Nanomaterials That Indicate Risks Risks associated with ENMs will depend on the level and time course of exposure and on the properties of ENMs to which an organism is exposed. Ex- posure models, whether screening-level models, such as the Environmental Pro- tection Agency Exposure Fast Assessment Screening Tool (EPA 2010a,b), or more detailed models, such as Total Risk Integrated Methodology (TRIM FaTE, EPA 2010c), require information regarding ENM sources, transport, transforma- tions, fate, and bioavailability (Johnston et al. 2010). Each of those has consid- erable uncertainty, and in many cases the tools needed to characterize them for measuring or monitoring exposure potential are lacking. Specific research needs to decrease uncertainty in exposure models are described below. Sources of Engineered Nanomaterials in the Environment The expected concentration of ENMs in environmental compartments cannot be predicted without reasonable estimates of the quantity of ENMs re- leased and an understanding of the medium into which they are released (for example, air or water), their physical and chemical properties, and the spatial and temporal distribution of the releases. The committee’s conceptual framework for understanding EHS aspects of ENMs (Figure 2-1) uses an integrated value-chain and life-cycle construct as the basis of understanding of the potential for and nature of releases of and expo- sures to nanomaterials. That framework entails the conduct of research to iden- tify and elucidate in considerable detail a full or at least representative array of nanomaterial value chains and life cycles. These steps also are critical to evalu- ating the plausibility and potential severity of risks associated with ENMs re- leased to the environment (Chapter 2). Many of the tools needed to predict exposure to ENMs will take time to construct. Market research is a valuable tool that can be used now to identify ENMs that are most likely to be developed in the near term. Market analysis can be used to identify key market sectors; to determine the types of nanomaterials, nanoenabled intermediates, and end products that will probably enter the market in the near term; and to estimate the volumes of materials produced, imported, and exported for specific regions. Together, those data can be used to estimate the ENMs that have the greatest potential for human and environmental expo- sure. The value chain for ENMs includes many steps: synthesis, packaging, handling, shipping, and finally incorporation into intermediate and final on- sumer and industrial products. Predicting human exposure to ENMs and releases into the environment requires a better understanding of those processes, includ- ing  Manufacturing processes and handling practices.  Postmanufacture processing.  Storage, distribution, and transport.  Numbers of workers involved and the nature of their activities.

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 121  Wastes and byproducts generated and how they are managed.  Miscellaneous routine and nonroutine activities, such as maintenance and cleaning of production equipment, upsets, and disruptions or accidents. The potential for exposure to ENMs and their release into the environment will be influenced by the type of material; the type of application (industrial, commercial, or consumer); intended uses and reasonably expected unintended uses, including the potential to become airborne; and the potential for accidental releases over a product’s life cycle. Market research can assess the potential use scenarios for specific ENMs to determine whether they are likely to be released into the environment or result in unintended human exposure. Other considera- tions for release potential include  User habits and practices (for example, frequency and duration of use or misuse).  Ancillary activities (for example, maintenance and repair).  Wear, deterioration, and aging (for example, breakdown of exposed coatings). End-of-use considerations include disposal, recycling of ENMs within new materials, and reuse of materials. All those present different potentials for exposure and release into the environment, and each should be determined for the types of ENM-enabled products expected on the market and their potential for release. Releases should be characterized along the value chain of the materials to determine the most likely environmental compartments and locations to be af- fected and to estimate the expected concentration of ENMs in those media. A framework for determining release inventories from identified primary sources of ENMs (for example, wastewater-treatment plant effluent, biosolids, and stack emissions) should be developed. Methods for quantifying and characterizing ENMs in each source stream should be developed to validate models that have been constructed to predict ENM environmental releases. The models should be informed by large-scale efforts, such as the Nanomaterial Registry that is being supported by the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Environmental Health Sciences, and the National Can- cer Institute (Ostraat 2011) to collect information on nanomaterials. Additional models will need to be developed for specific release scenarios. Research Needs for Assessing Sources of Engineered Nanomaterials in the Environment  Assess current and future markets for nanotechnology, identifying nanomaterials, intermediate materials, and products made with nanomaterials and nanoenabled end products that are on the market, are under development, or can be expected to emerge over the next 5-10 years.

122 Identifying Properties of Engineered Nanomaterials That Indicate Risks  Identify the processes used to manufacture and distribute nanomateri- als and nanoenabled intermediate and end products.  Determine and categorize nanomaterial applications, product uses, and end-of-life scenarios for ENMs.  Determine and categorize potential for releases of and exposures to ENMs.  Develop models for predicting releases of ENMs into the environment along the material’s life cycle and value chain. Transport, Transformation, and Persistence of Engineered Nanomaterials Once released into the environment, ENMs will be transported away from the source and distribute among the environmental compartments (for example, air, water, soil, sediment, and biota). Several factors probably most influence ENM transport and fate, including the location of the release, aggregation or disaggregation, and attachment to environmental surfaces. To aid in near-term risk management of ENMs in the environment, the transport components of ex- posure models must be modified to include processes relevant to ENMs that are expected to behave as particles rather than as molecules. The effects of attached macromolecules or ENM matrix components, and especially NOM, on ENM aggregation and deposition need to be considered. The interrelationship between ENM properties and the media in which ENMs are dispersed (for example, freshwater, seawater, and wastewater) need to be included. Exposure models need to be updated to improve estimation of the dilution behavior of ENMs re- leased into the environment, because the choice of assumptions about dilution will influence the prediction of ENM concentrations by the models. The models need to include aggregation, deposition, and sedimentation. A set of standard- ized test methods (described previously) is needed to identify the ENM proper- ties that best predict their transport in the environment. Ultimately, comprehensive transport models specific to ENMs must be developed and validated to determine transport away from sources and dilution in the environment, for example, modules specific to runoff from agriculture due to ENMs in biosolids applied to the fields; ENM dry and wet deposition from air, sedimentation, and sediment transport; and groundwater infiltration from agricultural activities. As discussed in Chapter 3, ENM transformations in the environment may lead to products that have transport and toxicity characteristics different from those of their parent materials (Cheng et al. 2011), and that distribute differently in the environment. To incorporate transformations into exposure models, the likely transformations need to be determined for the different classes of materi- als, and the appropriate parameters for incorporating the transformations and persistence into exposure models also need to be determined. Metrics are needed for describing the extent of ENM transformation and the persistence of ENMs. For example, a simple half-life time for loss of ENM mass may be appropriate

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 123 for ENMs that dissolve, but more complex metrics such as size, change in num- ber concentration, or change in reactivity with time may be more appropriate for ENMs that only partially transform. Research Needs for Assessing Transport and Fate of Engineered Nanomaterials in the Environment  Modify exposure models to include processes most relevant to assess- ing ENM distribution in the environment and human exposure (for example, aggregation, degradation rate, and dilution).  Incorporate into exposure models metrics for transformation and per- sistence (for example, half-life time, size, change in number concentration or surface area, or change in reactivity with time). MODELS FOR PREDICTING HUMAN HEALTH, ORGANISMAL, AND ECOLOGIC EFFECTS As discussed in Chapter 3, a key requirement for use of any in vitro assay as a predictive tool is that the underlying mechanisms also operate in vivo. For human health and ecosystem considerations, there are at least four generally recognized toxicity mechanisms: inflammation and oxidative stress, immu- nologic mechanisms, protein aggregation and misfolding, and DNA-damage mechanisms. Effects models should consider each of those rather than relying solely on oxidative stress end points. In addition, there may be other mecha- nisms that have yet to be identified. The sections below discuss modeling needs for assessing ecosystem effects. A major ecotoxicology modeling goal has been the development of reli- able, predictive models whereby the chemical structure of a compound can be used to predict the harm that it will cause. That is particularly challenging for ENMs given the breadth of ENM types and the lack of understanding of ENM transformations in the environment and in organisms. Toxicity mechanisms of ENMs should be a major research focus to augment the models. Predictive mod- els are most accurate when a specific mechanism is being probed, whereas a whole-organism response in the absence of knowledge of the mechanism pro- vides poor modeling and predictions (Schmieder et al. 2003; Ankley et al. 2010). Developing assays that provide unbiased parameters and that elucidate dif- ferent mechanisms of action will support better models. Data should include multiple end points for a chronic life-cycle assessment. Low-dose effects need to be assessed. Multiple organisms need to be considered, as do multiple pathways. To that end, more information is needed on the pathways that are disrupted in whole-organism assays. Duration of exposure needs to be considered as part of the effects model because these effects may change over time as a result of ac-

124 Identifying Properties of Engineered Nanomaterials That Indicate Risks cumulation or formation of byproducts in the organism or the recovery path- ways. Chronic and sublethal endpoints such as effects on interactions among species, species-community assemblages, biodiversity, and ecosystem function should be considered (Bernhardt et al. 2010). Research Needs for Predicting Organismal, Population, and Ecosystem Effects  Improve development of toxicity models by measuring and reporting on more sublethal toxicity end points—including, growth, behavior, reproduction, development, and metabolism—in more ENMs that have specific core and sur- face properties.  Develop models to link the biochemical pathway responses to ENMs and ENM properties (beyond oxidative stress) to adverse outcomes.  Develop models that can predict organismal, population, and ecosys- tem effects of exposure to ENMs through the collection of more data on commu- nity and ecosystem effects and the determination of pathways for adverse out- comes (for example, effects on survival and reproduction). EXPOSURE TO DOSE MODELS Models can be developed to predict the concentrations of ENMs in various environmental media (for example, air, water, soil, and sediment) and thus to predict exposure. Dosimetry is needed to correlate measurable exposure concen- trations with adverse outcomes observed in exposed organisms. Dosimetry is organism-dependent and therefore difficult to predict without organism-specific models; however, decisions about acceptable concentrations of ENMs in envi- ronmental media or acceptable worker exposure will require understanding of relationships between ENM properties, environmental conditions, routes of ex- posure, and doses to an organism. These considerations extend to models of both human and environmental exposures. Ultimately, dosimetry models must be developed to predict dose from exposure concentrations. Existing exposure models need to be updated to be applied to ENMs. As discussed in Chapter 3, human inhalation exposure to ENMs is an important route of exposure to humans. Following uptake of ENMs, they may be distrib- uted throughout an organism and reside in locations distal to the initial exposure site. Exposure models, such as the Multiple Pass Particle Dosimetry model need to be updated to include the effects of different particle shapes and translocation from the deposition site in the respiratory tract to other organs. Biodistribution models are essential for identifying specific organs that may be targeted, injury mechanisms, and the toxicity assays that best represent the exposures and mechanisms of toxicity. A repository of validated reference or benchmark nanomaterials, whose surfaces can be modified, should be established to simu- late the effects of diverse surface properties on their disposition; that will help to

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 125 assess biodistribution in animal models after exposure by different routes. Spe- cifically, the influence of exposure concentration on biodistribution should be investigated. Establishing a comprehensive biodistribution model—including uptake, translocation, and elimination pathways and mechanisms—will be an important input for bioinformatics. Because ENMs will probably be present in environmental media at very low concentrations, acute toxicity may not be a primary concern. However, or- ganisms may be exposed to ENMs at low concentrations for long periods. A long-term goal is to predict ENM bioavailability to and bioconcentration in rele- vant organisms on the basis of properties of the ENMs and their transformation products. That is a formidable task because bioavailability and bioconcentration will probably depend in part on ENM properties, route of exposure, and disper- sion media. Thus, the ENM properties and environmental conditions affecting bioavailability and bioconcentration of ENMs in long-term exposure need to be determined and incorporated into exposure models. Research Needs for Developing Exposure-to-Dose Models  Update dosimetry models by determining deposition efficiency and un- derlying mechanisms of inhaled ENMs throughout the respiratory tract depend- ing on shape, surface properties, and agglomeration of the ENMs.  Support development of biodistribution models by identifying reference or benchmark ENMs with appropriate labels to serve as models for assessing disposition after exposure by different routes (in air, water, and food).  Develop models to predict bioavailability of ENMs on the basis of their properties, routes of exposure, and exposure media. Model Uncertainty The uncertainty surrounding environmental exposure to and effects of ENMs is substantial given the paucity of data on the behavior of ENMs in the environment and the measured quantities of ENMs in environmental media. Research efforts may never decrease inherent uncertainties to the point where deterministic models are possible. Because of the high degree of uncertainty regarding the ENM properties that influence fate and exposure potential, the use of probabilistic exposure-assessment models is needed. That is not unlike the risk-informed decision-making (RIDM) approach used by the Nuclear Regula- tory Commission (Vietti-Cook 1999). RIDM, as defined by the commission, is an approach to regulatory decision-making in which insights from probabilistic risk assessment are considered with other engineering insights. The approach asks simply, What can go wrong? How likely is it? What are the consequences? (Vietti-Cook 1999). A long-term goal is to decrease uncertainty in results of exposure and ef- fects models to better support decision-making with regard to nanotechnology-

126 Identifying Properties of Engineered Nanomaterials That Indicate Risks related EHS risks. Approaches to identifying research that will provide the greatest reduction in uncertainty in exposure modeling may benefit from a value-of-information analysis as described in NRC (2009). Models used to predict exposure to and effects of ENMs must be capable of incorporating the uncertainties of the input parameter values to ensure that model results are expressed in the context of the uncertainties. Stakeholders and regulators who make risk-management decisions regarding ENMs will need to become familiar with probabilistic models and interpretation of their results. Research Needs for Incorporating Uncertainty into Models and Reporting Uncertainty in Exposure Modeling  Identify key uncertainties surrounding exposure-assessment models and estimate the ranges of the uncertainties.  Incorporate uncertainty into models that are being developed to esti- mate sources, model transport and fate, bioavailability, and effects. INFORMATICS Predicting the potential effects of ENMs on the basis of their chemical properties will require a long-term funding commitment to nanotechnology- related EHS research and a highly coordinated research effort with standardized data collection and warehousing that allow mining of a highly diverse set of data (and metadata) types and formats. It will require an appropriate informatics in- frastructure that addresses the primary research needs discussed above and that supports more efficient approaches to increasing collaboration and data-sharing among the disciplines involved in nanotechnology research, development, trans- lation, and regulation. The previous sections of this chapter addressed major research needs re- sulting from a lack of information on  The availability of reference nanomaterials.  The characterization of nanomaterials as reported in the literature and in publicly available databases.  Errors and uncertainty in the methods and protocols used to produce the data.  The sensitivity of the methods to variations in experimental apparatus, materials, and procedures.  Errors and uncertainty in and the sensitivity of the models used to evaluate ENM structure-property relationships, to predict their behavior and effects, and to evaluate and manage risks. Although the nanotechnology community is distinguished by the wide spectrum of disciplines involved, the lists of research needs presented here could

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 127 be shared to some degree with any emerging technology that, by definition, is beginning to produce new and as yet insufficiently tested products. In particu- lar, errors and uncertainty in and the sensitivity of the methods and models used should be established because they are needed for improving product and proc- ess design and for predicting and managing risk. The current need to manage life-cycle risk posed by nanotechnology products presents an opportunity to establish an infrastructure that can serve as an exemplar of emerging technolo- gies. Nanotechnology and nanoscience span basic and applied research and translational and regulatory domains, including manufacturing, process control, and human and environmental health. The timescales for developing new stan- dard methods from available research protocols is normally decades. For nanotechnology, the timescales must be compressed dramatically because of the introduction of so many new products and components that contain nanomateri- als. Sharing information among these broad and diverse domains requires atten- tion to ensure that the information communicated is interpreted properly and unambiguously and that the transmission is accomplished within the appropriate timescales and resources. Although modern information technology offers un- precedented tools and applications for rapid communication, data storage, transmission of semantic content, and support for collaborative enterprises, technology alone cannot provide the needed solutions. New legal, social, and cultural approaches and mechanisms will be required to permit more compre- hensive and time-appropriate information-sharing as nanotechnology products continue to proliferate. In 2004, international efforts to standardize nanotechnology were initiated and emphasized the need for standard analytic methods and protocols for char- acterizing the physicochemical properties of nanomaterials and their activity in in vitro and in vivo studies and the need for common terminologies to harmo- nize communication among different disciplines and stakeholders (OECD 2010; IANH 2011). Additional efforts followed quickly, including development of standards for the minimum information required for characterization of nanoma- terials (Aitken et al. 2009; Card and Magnuson 2009; MINChar 2009; Boverhoff and David 2010), for taxonomies and ontologies to augment metadata with se- mantic content about nanomaterial properties (Gordon and Sagman 2003; Ko- zaki et al. 2011; Thomas et al. 2011), and for harmonization of formats for data- sharing (ASTM 2010; Klemm et al. 2010). The need for new approaches to provide the requisite informatics infra- structure are described here with the need for information-sharing to provide an understanding of the collaboration timescales, information technologies, and resources required. Approaches and informatics requirements are described as they are related to method development and validation, model development and validation, and data management and data-sharing. Research priorities to de- velop the knowledge base and data-sharing capabilities are presented in Chapter 5. Means of enhancing collaboration necessary for implementation of an infor- matics infrastructure are discussed in Chapter 6.

128 Identifying Properties of Engineered Nanomaterials That Indicate Risks Method Development and Validation Standard methods and instrumentation developed for nanomaterials re- search must be adapted to process control for manufacturing, recycling, waste processing, regulation, and remediation. In addition, documentation on standard guidelines and practices is needed. Standard-method (protocol) development is difficult. The development and validation of standard methods is a long process that requires exhaustive testing of the precision, accuracy, reliability, and repro- ducibility of the methods and of the sensitivity of results to changes in protocol parameters, instrumentation, environment, media, and models (that is, the rug- gedness and robustness of the method). Standard-development organizations (SDOs) require years to reach consensus on new standards, and testing protocols to obtain measures of their error and uncertainty through interlaboratory studies (ILSs) requires additional time and resources. Reference nanomaterials for ILSs, instrument calibration, and validation are generally not available, particularly in large, well-characterized batches with sufficient stability. In addition, shipping the reference and sample nanomaterials, cell lines, media, and materials required by a protocol and materials needed for sample preparation may require envi- ronmentally controlled shipping containers and data-logging devices to ensure that the materials are not exposed to extreme conditions in transit. Gauging ad- herence to standard methods is also a problem because of the difficulty of pro- viding a documented standard with sufficient detail regarding necessary addi- tional positive or negative controls and sample preparation, and because of the lack of any data-reporting standard regarding deviations from the method. In- volvement in SDOs is a voluntary activity: industry has incentives to participate in standards development, but academic participation, at least in the West, is hindered by the lack of funding and academic credit for participation in standard development (CTAC 2007; OSI 2007). Collaboration among SDOs is also lack- ing and is usually confined to postdevelopment harmonization of standards. Because of those compounded difficulties in the development and dis- semination of validated standard methods, recent ILSs of new protocols by the Asia Pacific Economic Forum, the American Society for Testing and Materials, and the International Alliance for NanoEHS Harmonization have shown that the reliability and reproducibility of published nanotechnology data are problematic (Hackley et al. 2009; Murashov and Howard 2011). In addition, the ability to qualify laboratories in the performance of new validated methods is extremely restricted. As a result, contract research organizations (CROs) are not available to perform the extensive characterizations required, and individual laboratories must perform the measurements themselves. That leads to variability in charac- terization results and in inefficient use of funding for nanotechnology-related EHS research. However, it should be noted that outsourcing of material charac- terization by CROs may not be effective in all cases; for example, characteriza- tion efforts must be closely linked to synthetic efforts because rapid feedback is needed to develop the best materials, and this is not conducive to outsourcing. Given these challenges, the establishment and broad dissemination of best prac-

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 129 tices to support local characterization and real-time feedback to nanomaterial producers would significantly enhance data quality and consistency, without invoking standards and certified instruments that are prohibitively expensive. Needs in Method Development and Validation  Increase the amount, quality, and availability of nanomaterial charac- terization and effects data by accelerating the development of validated stan- dard methods and interlaboratory study of the methods.  Provide greater detail of the methods for sample preparation and re- quired controls for specific nanomaterials.  Remove the barriers to qualifying CROs to perform the needed exten- sive characterizations of nanomaterials by accelerating the development of these more detailed and validated standard methods and by ensuring environ- mental control of method materials and nanomaterial samples during shipping. Those general needs are of two types: (1) needs that can be addressed through traditional informatics methods, applications, and tools and (2) needs that require new approaches and mechanisms to ensure collaborative participa- tion. Informatics needs that require enhancement of traditional method development and validation procedures include the ability to collect, organize, curate, and share data on  The methods used, including links to standard protocols.  Deviations from the methods that were implemented, including addi- tional controls or sample-preparation techniques for specific nanomaterials.  Links to error, uncertainty, and sensitivity data on the methods as de- termined through the method-validation process and interlaboratory studies.  The level of validation and expertise for laboratories using the meth- ods.  Whether minimum characterization of nanomaterial standards were met in carrying out an investigation.  Links to training materials to assist laboratories in adopting new stan- dard methods and techniques. Providing a similarly concise categorization of new approaches and mechanisms to accelerate development and validation of new methods is diffi- cult primarily because current practices are deeply ingrained in different disci- plines and communities and shortening the timeframes for transitioning from pure hypothesis-driven research methods to a translational and regulatory method-validation framework will necessarily disrupt current practices. In short, cultural barriers need to be overcome, and the more tractable technical barriers

130 Identifying Properties of Engineered Nanomaterials That Indicate Risks to implementing a new informatics infrastructure need to be addressed. How- ever, documented examples of how to overcome these barriers through digital communication are available (Goble et al. 2010; Tan et al. 2010). Approaches needed for new collaborative mechanisms for method development and validation include the ability to provide a framework and additional incen- tives for  Broader participation in method development and validation, including interlaboratory studies, particularly among academics but also interinstitution, interagency, and international collaboration, including that of regulatory bod- ies, metrology institutes, and national laboratories.  Participation in responding to the specific informatics needs delineated previously while ensuring that data curation is performed by those with the most expertise in evaluating the quality of each particular dataset, that data rights are determined by the owners of the data, and that user requirements are pro- vided by all user communities, including nongovernment organizations and the public.  Increased collaboration and harmonization among standard- development organizations, contract research organizations, nanomaterial pro- viders, and organizations that conduct interlaboratory studies to develop meth- ods to make the most efficient use of the available pool of experts and the best available materials and to minimize the need for later efforts in harmonization among standards produced by different organizations. An implementation scenario for development of methods and protocols is described in Appendix B. Model Development and Validation The previous sections described the need for improving model develop- ment and validation efforts with regard to ENMs—models for predicting envi- ronmental release, transport and fate, exposures and their relation to dose, and human health, organismal, and ecologic effects—and for risk assessment and determination of quantitative structure-activity relationships. Each of the models incorporates submodels of different types—models of in situ environments; cel- lular, tissue, organ, system, organism, and ecosystem models; and models of ENM structure that use basic descriptors, detailed molecular structures, or both and that use different numerical and statistical applications and tools. Although it may appear that the requirements for model development and validation are similar to those for method development and validation, there is a striking dif- ference: the models are in a computer-usable form. That difference opens the possibility of more rapid, collaborative development and validation of models than can be achieved for methods. It is an encouraging distinction inasmuch as

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 131 the greater use of predictive models in conjunction with experimental results can help in discovering underlying mechanisms. The Worldwide Protein Data Bank (wwPDB) is a relevant example. The wwPDB was originally designed to serve both as a repository for protein mo- lecular structures and as a collaborative mechanism to curate and validate struc- tural models and to improve predictive models of protein structure, conforma- tion, binding, and activity in different environments (Berman et al. 2007). Although today the wwPDB is primarily a repository, the use of the structural models continues to be an important tool for improving and validating predictive models. A similar worldwide repository for molecular structures of ENMs that could validate predictive models is needed. Extending the PDB of nanomaterials concept to include a database of pre- dictive models would offer some desirable alternatives to current procedures. (A discussion concerning the challenges of developing such a database is described in Appendix B, under the heading Development and Validation Scenario.) Sci- entific collaboration in model development through publications imposes multi- year delays: a model is first developed or improved; new results are obtained and verified with the model; a publication is written, published, and read, and its findings are corroborated by other researchers; and a new improvement is made in the model. In an alternative scenario, in light of the PDB of nanomaterials concept, the initial researcher could make the predictive model available on the Web with all the files, run-time parameters, and test scripts necessary to dupli- cate the result—and save years. The technology to support such accelerated col- laboration is widely available, and credit can be given to both the model devel- oper and the person who improves the model. The advantages of faster, open access to scientific results have been well documented in physics (for example, Gentil-Beccot et al. 2009), and open-access collaborative networks have proven to be very effective in advancing biomedical research and translating the results to the clinic (Derry et al. 2011). In fact, collaborative code development is rec- ognized in industry as the preferred means of producing reliable computer appli- cations and is used in existing collaborations. Adapting the technique to model and submodel development and validation on an international scale would dra- matically shorten the timescale for model improvement. Such model- development practices would also enhance scientist-to-scientist collaboration on problems of mutual interest with few operational resources and provide more facile options for leveraging and sharing intellectual property through knowl- edge-sharing networks and sites such as Creative Commons and IC Tomorrow. The magnitude of the changes occurring in managing and using intellectual property are reflected in the Creative Industries Knowledge Transfer Network (2011) report, p. 30: The business model evidence…”indicates that the creative industries are being pushed increasingly towards realizing value from IP [intellectual prop- erty] sharing. The precedent of open source suggests that the highest value will be placed on IP that delivers scale through widespread adoption and use”.

132 Identifying Properties of Engineered Nanomaterials That Indicate Risks Informatics Needs for Model Development and Validation  An informatics portal similar to the wwPDB is needed to archive, or- ganize, curate, validate, and share structural models of nanomaterials and their surface coatings, both pristine and transformed, for collaborative use interna- tionally.  An extension of the database is needed to archive, organize, curate, validate, and share the predictive and probabilistic models and submodels to accelerate their development and use and to augment and complement experi- mental techniques.  New mechanisms are needed to aid in implementing the required col- laborative databases for structural models of ENMs and for development of predictive and probabilistic models. An implementation scenario for development of predictive and risk mod- els is discussed in Appendix B. Data-Sharing The preceding discussions highlighted the need for sharing data from spe- cific protocols; for example, for characterization of pristine and transformed ENMs in complex samples, for toxicity tests and ecosystem and population ef- fects, and for methods for exposure assessment and for characterizing trans- formed and weathered ENMs. The variety of protocols reinforces the need for data-sharing among diverse disciplines that use different techniques and prac- tices. It is important to provide data-sharing techniques that provide the scien- tific data requested and that describe both the data and the ENMs with sufficient detail to track which manufactured lot of a material the ENM samples were taken from to account for lot-to-lot variability. The informatics system should use specific nomenclatures and terms that have agreed-on definitions. The same requirements are appropriate for supporting model development and validation. Experience with today’s search engines, however, illustrates the lack of specificity that is achieved when only search terms are used—for example, the millions of “hits” that might have to be sifted through to extract the desired in- formation. Adding semantic content about the meanings and relationships of the search terms is the aim of the Semantic Web, sponsored by the World Wide Web Consortium of informatics systems providers and users (W3C Semantic Web 2011). Providing machine-usable logical relationships about and among search terms allows a search engine to reduce drastically the number of false “hits.” Ontologies improve the use of search terms by supplying definitions for each term and explicit logical relationships among the terms specified so that they can be interpreted and used by a computer. The effort to generate and main- tain an ontology is usually supported by a community that agrees on the concept definitions and logical relationships. Ontologies can be modified or extended to

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 133 accommodate different communities, and methods exist to map relationships between terms in different ontologies, allowing any (mapped) ontology to be used to mine data in a dataset organized by terms of a different ontology. Cur- rently, organizations involved in nanotechnology, both nationally and interna- tionally, support Web sites and portals to provide information and analyzed data. Very few portals offer raw data that may be stored locally in the laboratory gen- erating the data. Most of the portals use their own systems and offer their infor- mation through current search engines. Attempting to harmonize the search terms, data formats, curation levels, and security for these portals would entail a large enterprise that would be prone to failure because the databases may be linked to back-office applications that would be difficult to modify. Moving all the data to a central site has been tried and is usually very difficult because of issues involving data rights and security and the need to agree on common for- mats, procedures, and rules for governance. Informatics Needs for Data-Sharing  Use existing pilots to demonstrate the capability to federate the differ- ent sites through the use of semantic web technologies, including ontology de- velopment to enable data curation by experts in the data, and access control by the owners of the data. Using that method would allow international entities to come together on an equal footing to craft a short-term solution for collaborative protocol and model development. A modest effort would be needed to demonstrate current capability as a pilot project for use in an interoperable system to establish user requirements relevant to the entire community, and initial efforts are being un- dertaken within the nanotechnology informatics community (InterNano 2011).  Use and modify existing ontologies and semantic web applications, perhaps in collaboration with search-engine providers, to develop an automatic ontology “crawler” to update mappings among the ontologies used or adopted by the collaborating partners. Barriers to Informatics Successful implementation of the informatics strategy described in this chapter—including developing ontologies, data-sharing, and community model development—requires appropriate datasets as inputs. The emerging field of nanoinformatics, in contrast with the more fully developed field of bioinformat- ics, faces some specific challenges. Biopolymers are often discrete structures or sequences, whereas nanomaterials typically exhibit a dispersion of sizes, com- positions, and surface coatings. Such dispersions are difficult to define and re- duce to the precise code needed for informatics. Second, given the wide array of nanomaterial types, structural information for different classes of materials will

134 Identifying Properties of Engineered Nanomaterials That Indicate Risks be based on different sets of analytic measurements that make direct compari- sons difficult. Because no one measurement can describe a nanomaterial com- pletely, an informatics approach will need to synthesize the information from multiple techniques to describe the material. Given the number of gaps in the data on the nanomaterials described in the literature, most materials are now incompletely described and will probably remain so unless incentives are devel- oped to characterize them. Finally, whereas biopolymers can be readily de- scribed by reference to their primary sequence and a series of letter codes or by a defined three-dimensional structure determined with x-ray crystallography, the different types of measurements (for example, images, histograms, optical spec- tra, and elemental composition) that are used to define nanomaterials are diffi- cult to reduce to code. Those complexities will result in barriers to the development of nanoin- formatics unless they are addressed through close interaction with the scientists who are producing and characterizing the new nanomaterials. One barrier is the relatively onerous process of data entry for nanomaterials. If the materials can- not be described as single structures or sequences, as is possible for biopoly- mers, describing their dispersity makes the process more time-consuming. In addition, uploading raw data that are in a wide array of nonstandard formats presents a barrier to those who might contribute to the database of materials. But it is important to have access to the raw data because producing a numerical descriptor from them often involves considerable interpretation. Who will generate the data for informatics, and what are the incentives for them to participate? From one perspective, the information used to populate the databases for nanoinformatics efforts will be developed by specialists using standard protocols and working with defined reference materials. That approach is relatively slow—working with one painstakingly produced and characterized material at a time. More rapid progress could be made if information on all ma- terials produced and characterized could be captured in the databases regardless of who produces the materials. The presence of such data would encourage bi- ologists and toxicologists to study the materials, but what is the incentive for the nanomaterials chemist to contribute this information? Recommendations for addressing barriers to informatics for nanomaterials: Provide incentives to nanomaterials innovators to characterize and report suffi- cient analytic data to define materials for comparison with other materials, in- cluding error, uncertainty and sensitivity data. For example,  Journals could require the data for publication.  Agencies could make collecting and sharing the data conditions for funding, perhaps through National Science Foundation data-management plans (see discussion in Chapter 6) or more specifically in nanotoxicology grants.

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 135 Recognize the challenges in comparing data. For example, size and size distri- butions from transmission electron microscopy are not all the same. They are not the raw data; the image is. Although it is necessary to obtain a representa- tive sample from a set of images, new standard methods for nanomaterials (for example, NIST/NCL 2010; ASTM 2011) reference best practices to control im- age selection bias (for example, Allen 1996; Jillavenkatesa et al. 2001), and evaluations of bias in instrumentation software for defining particle boundaries are being considered. It is difficult to develop structure-activity relationships when the structures are not concretely defined. Reduce barriers to nanomaterial innovators contributing to databases by engag- ing with them, understanding the complexities, and finding solutions that reduce the barriers. Provide incentives for companies to provide information on nanomaterials that they have pioneered. This will require finding creative ways to protect intellec- tual property. Work toward a model, such as the PDB of nanomaterials concept, but engage nanomaterial-synthesis experts at the beginning to identify and find solutions to obstacles. TABLE 4-1 Summary of Research Needs Identified in Chapter As Mapped to the Tools MATERIALS Well-characterized materials are needed, including: reference materials of varied size, shape, aspect ratio, surface charge, and surface functionality for testing; “real-world” materials for testing; “weathered” nanomaterials that are representative of those expected in vivo or in situ; materials that can be tracked (for example, for biodistribution or environmental partitioning studies) without introducing experimental artifacts in exposure and toxicity studies; and standard reference materials to use in calibrating assays and measurement tools. METHODS Develop and validate new or modify existing standard toxicity-testing protocols for ENMs, including relevant cell types and organisms, appropriate dosimetry and toxicity end points (for example, chronic effects), and gene and protein expression to identify and validate toxicity mechanisms, such as biodistribution of ENMs and toxicity-pathway models. Develop methods to extrapolate and predict long-term low-dose effects from short-term high-dose effects, and validate their accuracy through blinded test methods. Develop screening methods that can indicate the potential for bioavailability and potential for effects due to chronic ENM exposure or for indirect effects, that is, not direct toxicity from ENM exposures (for example, the effects of ENMs on carbon and nitrogen cycling). Develop and validate standard methods for measuring and reporting attachment affinities of ENMs to biologic and environmental surfaces to facilitate assigning values to parameters in exposure models. Develop methods to determine the reactivity and stability of ENMs in biologic and environmental samples, including standard measures for assessing and reporting reactivity (for example, generation of reactive oxygen species). (Continued)

136 Identifying Properties of Engineered Nanomaterials That Indicate Risks TABLE 4-1 Continued Develop a standardized approach for measuring a method’s sensitivity to changes in important variables (for example, pH, ionic strength, organic matter, and biomacromolecules) and standard ways to report sensitivity. INSTRUMENTATION Develop new instrumentation and methods for existing instrumentation to isolate subpopulations of ENMs from polydisperse samples. Develop tools that can detect ENMs, especially at low (relevant) concentrations in situ or in vivo, followed by methods to track and characterize ENM properties (for example, reactivity, reactive surface area, nanometer and subnanometer surface features, aggregation, and adsorption of organic macromolecules). In the future, develop methods that operate unattended and monitor ENMs in the environment in different media, especially air and water. Develop tools to assess the rate and degree of transformation of ENMs in vivo or in situ, especially specific alteration of surface properties of ENMs due to adsorption of proteins and lipids (corona formation) and NOM. MODELS Develop models to estimate sources of ENMs released into the environment along a material’s life cycle and value chain. Modify traditional exposure models to include processes that affect ENM distribution in the environment and influence human exposure (for example, attachment to environmental and biologic surfaces, degradation rate, and dilution) and determine how to assign values to parameters in those models. Determine toxicity pathways for outcomes (for example, effects on survival and reproduction) that predict population effects of ENM exposure and formulate ecotoxicity models, using data on sublethal toxicity end points (including effects on growth, behavior, reproduction, development, and metabolism). Update inhalation models to include dependence on ENM shape, surface properties, and agglomeration on deposition efficiency, and the underlying mechanisms of deposition of inhaled ENMs in the respiratory tract. Identify pathways of elimination of ENMs after their biodistribution and accumulation in primary and secondary organs. Determine principle mechanisms of elimination as inputs into predictive bioinformatics modeling. Identify key uncertainties and sensitivities surrounding exposure assessment and effects models, estimate the ranges of the uncertainties and sensitivities, and incorporate the uncertainties into the models. INFORMATICS Identify minimum characterization principles to develop standardized descriptors (that is, metadata) for ENMs that are related to their key physical material characteristics for reporting and cross-referencing data on ENM properties and effects. Establish uniform metadata to describe ENM manufacturing and distribution processes and to correlate lot- to-lot variability of ENM properties with changes in synthesis and handling. Develop ontologies and data formats to allow relevant data on gene and protein expression to be correlated with ENM-toxicity mechanisms. Develop strategies for federating nanotechnology databases administered by different agencies, business entities, universities, and nongovernment organizations to allow seamless data exposure and data-sharing while protecting intellectual-property rights. Develop new mechanisms for digital archiving and annotating and updating of methods, data, tools, and models to spur rapid and efficient formation of new targeted national and international scientific collaborations. Develop and augment ontologies to support nanotechnology and nanoscience and in particular to develop an ontology “crawler” to aid in mapping relationships among ontologies.

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 137 REFERENCES Aitken, R.J., P. Borm, K. Donaldson, G. Ichihara, S. Loft, F. Marano, A.D. Maynard, G. Oberdörster, H. Stamm, V. Stone, L. Tran, and H. Wallin. 2009. Nanoparticles - one word: A multiplicity of different hazards. Nanotoxicology 3(4):263-264. Allen, T. 1996. Particle Size Measurement, Vol. 1. Powder Sampling and Particle Size Measurement, 5th Ed. London: Chapman & Hall. Alvarez, P.J., V. Colvin, J. Lead, and V. Stone. 2009. Research priorities to advance eco- responsible nanotechnology. ACS Nano. 3(7):1616-1619. Ankley, G.T., R.S. Bennett, R.J. Erickson, D.J. Hoff, M.W. Hornung, R.D. Johnson, D.R. Mount, J.W. Nichols, C.L. Russom, P.K. Schmieder, J.A. Serrrano, J.E. Tietge, and D.L. Villeneuve. 2010. Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environ. Toxicol. Chem. 29(3):730-741. ASTM. 2010. ASTM WK28974 - New Specification for a Standard File Format for the Submission and Exchange of Data on Nanomaterials and Characterizations. ASTM International, West Conshohocken, PA [online]. Available: http://www.astm.org/ DATABASE.CART/WORKITEMS/WK28974.htm [accessed June 8, 2011]. ASTM. 2011. ASTM WK29480 - New Guide for Size Measurement of Nanoparticles Using Atomic Force Microscopy (AFM). ASTM International, West Consho- hocken, PA [online]. Available: http://www.astm.org/DATABASE.CART/WORK ITEMS/WK29480.htm [accessed Nov. 23, 2011]. Bartosiewicz, M.J., D. Jenkins, S. Penn, J. Emery, and A. Buckpitt. 2001a. Unique gene expression patterns in liver and kidney associated with exposure to chemical toxicants. J. Pharmacol. Exp. Ther. 297(3):895-905. Bartosiewicz, M., S. Penn, and A. Buckpitt. 2001b. Applications of gene arrays in environmental toxicology: Fingerprints of gene regulation associated with cadmium chloride, benzo(a)pyrene, and trichloroethylene. Environ. Health Perspect. 109(1):71-74. Berman, H., K. Henrick, H. Nakamura, and J.L. Markley. 2007. The worldwide Protein Data Bank (wwPDB): Ensuring a single, uniform archive of PDB data. Nucleic Acids Res. 35 (suppl. 1):D301-D303. Bernhardt, E.S., B.P. Colman, M.F. Hochella, Jr., B.J. Cardinale, R.M. Nisbet, C.J. Richardson, and L. Yin. 2010. An ecological perspective on nanomaterial impacts in the environment. J. Environ. Qual. 39(6):1954-1965. Bottero, J.Y., and M.R. Wiesner. 2010. Considerations in evaluating the physicochemical properties and transformations of inorganic nanoparticles in water. Nanomedicine 5(6):1009-1014. Bouwmeester, H., I. Lynch, H.J. Marvin, K.A. Dawson, M. Berges, D. Braguer, H.J. Byrne, A. Casey, G. Chambers, M.J. Clift, G. Elia, T.F. Fernandes, L.B. Fjellsbø, P. Hatto, L. Juillerat, C. Klein, W.G. Kreyling, C. Nickel, M. Riediker, and V. Stone. 2011. Minimal analytical characterization of engineered nanomaterials needed for hazard assessment in biological matrices. Nanotoxicology 5(1):1-11. Boverhof, D.R., and R.M. David. 2010. Nanomaterial characterization: Considerations and needs for hazard assessment and safety evaluation. Anal. Bioanal. Chem. 396(3):953-961. Bzdek, B.R., C.A. Zordan, G.W. Luther, and M.V. Johnston. 2011. Nanoparticle chemi- cal composition during new particle formation. Aerosol Sci. Tecnol. 45(8):1041- 1048.

138 Identifying Properties of Engineered Nanomaterials That Indicate Risks Card, J.W., and B.A. Magnuson. 2009. Proposed minimum characterization parameters for studies on food and food-related nanomaterials. J. Food Sci. 74(8):vi-vii. Casals, E., T. Pfaller, A. Duschl, G.J. Oostingh, and V. Puntes. 2010. Time evolution of the nanoparticle protein corona. ACS Nano. 4(7):3623-3632. Cheng, Y.W., L.Y. Yin, S. Lin, M. Wiesner, E. Bernhardt, and J. Liu. 2011. Toxicity reduction of polymer-stabilized silver nanoparticles by sunlight. J. Phys. Chem. C 115(11):4425-4432. Creative Industries KTN (Knowledge Transfer Network). 2011. Beacon 10 IP & Open Source, Final report. Creative Industries Knowledge Transfer Network, University of Arts, London [online]. Available: https://connect.innovateuk.org/c/document_ library/get_file?p_l_id=1342553&folderId=1812583&name=DLFE-33289.pdf [accessed Nov. 10, 2011]. CTAC (Clinical Trials Advisory Committee). 2007. First Clinical Trials Advisory Com- mittee Meeting, January 10, 2007, Bethesda, MD. National Institutes of Health, National Cancer Institute [online]. Available: http://deainfo.nci.nih.gov/advisory/ ctac/0107/10jan07mins.pdf [accessed May 25, 2011]. Derry, J., L.M. Mangravite, C. Suver, M. Furia, D. Henderson, X. Schildwachter, J. Izant, S.K. Sieberts, M.R. Kellen, and S.H. Friend. 2011. Developing predictive molecular maps of human disease through community-based modeling. Nat. Prec. 713 (April 4, 2011): doi:10.1038/npre.2011.5883.1. Dondero, F., M. Banni, A. Negri, L. Boatti, A. Dagnino, and A. Viarengo. 2011. Interactions of a pesticide/heavy metal mixture in marine bivalves: A transcriptomic assessment. BMC Genomics 12(1):195. Ehara, K., and H. Sakurai. 2010. Metrology of airborne and liquid-borne nanoparticles: Current status and future needs. Metrologia 47(2):S83-S90. EPA (U.S. Environmental Protection Agency). 2010a. Exposure and Fate Assessment Screening Tool Version 2.0 (E-FAST V2.0) [online]. Available: http://www.epa. gov/opptintr/exposure/pubs/efast.htm [accessed May 8, 2011]. EPA (U.S. Environmental Protection Agency). 2010b. Interim Technical Guidance for Assessing Screening Level Environmental Fate and Transport of, and General Population, Consumer, and Environmental Exposure to Nanomaterials. U.S. Envi- ronmental Protection Agency. June 17, 2010 [online]. Available: http://www.epa. gov/opptintr/exposure/pubs/nanomaterial.pdf [accessed Apr. 23, 2011]. EPA (U.S. Environmental Protection Agency). 2010c. Total Risk Integrated Methodol- ogy (TRIM) – TRIM.FaTE [online]. Available: http://www.epa.gov/ttn/fera/trim_ fate.html [accessed May 8, 2011]. Gao, X.H., L.L. Yang, J.A. Petros, F.F. Marshall, J.W. Simons, and S. Nie. 2005. In vivo molecular and cellular imaging with quantum dots. Curr. Opin. Biotechnol. 16(1):63- 72. Gentil-Beccot, A., S. Mele, and T.C. Brooks. 2009. Citing and reading behaviours in high- energy physics. How a community stopped worrying about journals and learned to love repositories. SLAC Scientific Documents No. 13693 [online]. Available: http:// slac.stanford.edu/pubs/slacpubs/13500/slac-pub-13693.pdf [access Nov. 23, 2011]. Gibson, N., U. Holzwarth, K. Abbas, F. Simonelli, J. Kozempel, I. Cydzik, G. Cotogno, A. Bulgheroni, D. Gilliland, J. Ponti, F. Franchini, P. Marmorato, H. Stamm, W. Kreyling, A. Wenk, M. Semmler-Behnke, S. Buono, L. Maciocco, and N. Burgio. 2011. Radiolabelling of engineered nanoparticles for in vitro and in vivo tracing applications using cyclotron accelerators. Arch. Toxicol. 85(7):751-773. Goble, C.A., J. Bhagat, S. Aleksejevs, D. Cruickshank, D. Michaelides, D. Newman, M. Borkum, S. Bechhofer, M. Roos, P. Li, and D. De Roure. 2010. myExperiment: A

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 139 repository and social network for the sharing of bioinformatics workflows. Nucl. Acids Res. 38:W677-W682. Gordon, N., and U. Sagman. 2003. Nanomedicine Taxonomy Briefing Paper. Canadian NanoBusiness Alliance, Toronto, Ontario. February 2003 [online]. Available: http://www.nanowerk.com/nanotechnology/reports/reportpdf/report31.pdf [accessed June 1, 2011]. Gottschalk, F., and B. Nowack. 2011. The release of engineered nanomaterials to the environment. J. Environ. Monit. 13(5):1145-1155. Gottschalk, F., T. Sonderer, R.W. Scholz, and B. Nowack. 2009. Modeled environmental concentrations of engineered nanomaterials (TiO2, ZnO, Ag, CNT, fullerenes) for different regions. Environ. Sci. Technol. 43(24):9216-9222. Hackley, V.A., M. Fritts, J.F. Kelly, A.K. Patri, and A.F. Rawle. 2009. Enabling stan- dards for nanomaterial characterization. Pp. 24-29 in INFOSM Informative Bulle- tin of the Interamerican Metrology System. August 13, 2009. Hamadeh, H.K., P.R. Bushel, S. Jayadev, O. DiSorbo, L. Bennett, L. Li, R. Tennant, R. Stoll, J.C. Barrett, R.S. Paules, K. Blanchard, and C.A. Afshari. 2002. Prediction of compound signature using high density gene expression profiling. Toxicol. Sci. 67(2):232-240. Hassellöv, M., J.W. Readman, J.F. Ranville, and K. Tiede. 2008. Nanoparticle analysis and characterization methodologies in environmental risk assessment of engi- neered nanoparticles. Ecotoxicology 17(5):344-361. Hong, H., Y. Zhang, J. Sun, and W. Cai. 2009. Molecular imaging and therapy of cancer with radiolabeled nanoparticles. Nano Today 4(5):399-413. IANH (International Alliance for NanoEHS Harmonization). 2011. International Alliance for NanoEHS Harmonization [online]. Available: http://www.nanoehsalliance.org/ sections/Home [accessed May 13, 2011]. InterNano. 2011. InterNano. Resources for Manufacturing. Nanoinformatics 2020 Road- map [online]. Available: http://eprints.internano.org/607/ [accessed Nov. 9, 2011]. Jarvie, H.P., H. Al-Obaidi, S.M. King, M.J. Bowes, M.J. Lawrence, A.F. Drake, M.A. Green, and P.J. Dobson. 2009. Fate of silica nanoparticles in simulated primary wastewater treatment. Environ. Sci. Technol. 43(22):8622-8628. Jeong, C.H., P.K. Hopke, D. Chalupa, and M. Utell. 2004. Characteristics of nucleation and growth events of ultrafine particles measured in Rochester, NY. Environ. Sci. Technol. 38(7):1933-1940. Jillavenkatesa, A., S.J. Dapkunas, and L.S.H. Lum. 2001. Particle Size Characterization. Special Publication 960-1. U.S. Department of Commerce, National Institute of Standards and Technology, Gaithersburg, MD [online]. Available: http://www.nist. gov/public_affairs/practiceguides/SP960-1.pdf [accessed Nov. 10, 2011]. Johnston, J.M., M. Lowry, S. Beaulieu, and E. Bowles. 2010. State-of-the-Science Report on Predictive Models and Modeling Approaches for Characterizing and Evaluating Exposure to Nanomaterials. EPA/600/R-10/129. U.S. Environmental Protection Agency, Washington, DC [online]. Available: http://www.epa.gov/athens/publica tions/reports/Johnston_EPA600R10129_State_of_Science_Predictive_Models.pdf [accessed Nov. 23, 2011]. Klaper, R., and M.A. Thomas. 2004. At the crossroads of genomics and ecology: The promise of a canary on a chip. BioScience 54(5):403-412. Klemm, J., N. Baker, D. Thomas, S. Harper, M.D. Hoover, M. Fritts, R. Cachau, S. Gaheen, S. Pan, G. Stafford, and D. Paik. 2010. nano-TAB: A Standard File Format for Data Submission and Exchange on Nanomaterials and Characterizations. Nanoinformatics

140 Identifying Properties of Engineered Nanomaterials That Indicate Risks Conference November 3-5, 2010, Arlington, VA [online]. Available: http://nanote chinformatics.org/posters [accessed Apr. 22, 2011]. Kozaki, K., Y. Kitamura, and R. Mizoguchi. 2011. Systematization of Nanotechnology Knowledge through Ontology Engineering: A Trial Development of Idea Creation Support System for Materials Design based on Functional Ontology. Poster Notes of the Second International Semantic Web Conference (ISWC 2003), October 20- 23, 2003, Sanibel Island, FL [online]. Available: http://www.ei.sanken.osaka- u.ac.jp/pub/kozaki/iswc2003pos_kozaki.pdf [accessed Apr. 22, 2011]. Kreuter, J. 1991. Nanoparticle-based drug delivery systems. J. Control. Rel. 16(1-2):169- 176. Leeuw, T.K., R.M. Reith, R.A. Simonette, M.F. Harden, P. Cherukuri, D.A. Tsyboulski, K.M. Beckingham, and R.B. Weisman. 2007. Single-walled carbon nanotubes in the intact organism: Near-IR imaging and biocompatibility studies in Drosophila. Nano Lett. 7(9):2650-2654. Lynch, I., T. Cedervall, M. Lundqvist, C. Cabaleiro-Lago, S. Linse, and K.A. Dawson. 2007. The nanoparticle - protein complex as a biological entity; A complex fluids and surface science challenge for the 21st century. Adv. Colloid Interface Sci. 134- 35:167-174. Metz, K.M., A.N. Mangham, M.J. Bierman, S. Jin, R.J. Hamers, and J.A. Pedersen. 2009. Engineered nanomaterial transformation under oxidative environmental condi- tions: Development of an in vitro biomimetic assay. Environ. Sci. Technol. 43(5):1598-1604. MINChar Initiative. 2009. Characterization Matters: Supporting Appropriate Material Characterization in Nanotoxicology Studies [online]. Available: http://characteriza tionmatters.org/ [accessed May 12, 2011]. Monopoli, M.P., D. Walczyk, A. Campbell, G. Elia, I. Lynch, F.B. Bombelli, and K.A. Dawson. 2011. Physical-chemical aspects of protein corona: Relevance to in vitro and in vivo biological impacts of nanoparticles. J. Am. Chem. Soc. 133(8):2525- 2534. Morawska, L., C. He, G. Johnson, H. Guo, E. Uhde, and G. Ayoko. 2009. Ultrafine parti- cles in indoor air of a school: Possible role of secondary organic aerosols. Environ. Sci. Technol. 43(24):9103-9109. Murashov, V., and J. Howard, eds. 2011. Pp. 196-197 in Nanotechnology Standards. Nanostructure Science and Technology Series. New York: Springer. Nel, A.E., L. Madler, D. Velegol, T. Xia, E.M. Hoek, P. Somasundaran, F. Klaessig, V. Castranova, and M. Thompson. 2009. Understanding biophysicochemical interac- tions at the nano-bio interface. Nat. Mater. 8(7):543-557. NIST/NCL (National Institute of Standards and Technology and Nanotechnology Char- acterization Laboratory). 2010. Measuring the Size of Nanoparticles Using Trans- mission Electron Microscopy (TEM). NIST-NCL Joint Assay Protocol, PCC-7. Version 1.1. U.S. Department of Commerce, National Institute of Standards and Technology, Gaithersburg, MD, and National Cancer Institute, Nanotechnology Characterization Laboratory, Frederick, MD [online]. Available: http://ncl.cancer.gov/NCL_Method_PCC-7.pdf [accessed May 12, 2011]. NRC (National Research Council). 2007. Toxicity Testing in the 21st Century: A Vision and a Strategy. Washington, DC: The National Academies Press. NRC (National Research Council). 2009. Science and Decisions: Advancing Risk As- sessment. Washington, DC: The National Academies Press. Oberdörster, G., A. Maynard, K. Donaldson, V. Castranova, J. Fitzpatrick, K. Ausman, J. Carter, B. Karn, W. Kreyling, D. Lai, S. Olin, N. Monteiro-Riviere, D. Warheit,

Environmental, Health, and Safety Aspects of Engineered Nanomaterials 141 and H. Yang. 2005. Principles for characterizing the potential human health effects from exposure to nanomaterials: Elements of a screening strategy. ILSI research foundation/Risk Science Institute Nanomaterial Toxicity Screening Working Group. Part. Fibre Toxicol. 2:8. OECD (Organisation for Economic Co-operation and Development). 2010. Guidance Manual for the Testing of Manufactured Nanomaterials OECD's Sponsorship Pro- gramme; First Revision. ENV/JM/MONO(2009)20/REV. Organization for Eco- nomic Co-operation and Development. June 2, 2010 [online]. Available: http://www.oecd.org/LongAbstract/0,3425,en_2649_34365_45409513_1_1_1_1,0 0.html [accessed Apr. 25, 2011]. Oostingh, G.J., E. Casals, P. Italiani, R. Colognato, R. Stritzinger, J. Ponti, T. Pfaller, Y. Kohl, D. Ooms, F. Favilli, H. Leppens, D. Lucchesi, F. Rossi, I. Nelissen, H. Thielecke, V.F. Puntes, A. Duschl, and D. Boraschi. 2011. Problems and chal- lenges in the development and validation of human cell-based assays to determine nanoparticle-induced immunomodulatory effects. Part. Fibre Toxicol. 8(1):8. OSI (OSI e-Infrastrustructure Working Group). 2007. Developing the UK’s e- Infrastructure for Science and Innovation, Report of the OSI e-Infrastructure Working Group, National e-Science Center. January 18, 2007 [online]. Available: http://immagic.com/eLibrary/ARCHIVES/GENERAL/NESC_UK/N070118O.pdf [accessed May 25, 2011]. Ostraat, M. 2011. The Nanomaterial Registry. Presentation at the Society for Toxicology Annual Meeting, March 6-10, 2011, Washington, DC [online]. Available: http://www.toxicology.org/isot/ss/nano/docs/Ostraat_guest_presentation.pdf [ac- cess May 12, 2011]. Petersen, E.J., Q.G. Huang, and W.J. Weber, Jr. 2008. Bioaccumulation of radio-labeled carbon nanotubes by Eisenia foetida. Environ. Sci. Technol. 42(8):3090-3095. Petosa, A.R., D.P. Jaisi, I.R. Quevedo, M. Elimelech, and N. Tufenkji. 2010. Aggregation and deposition of engineered nanomaterials in aquatic environments: Role of phys- icochemical interactions. Environ. Sci. Technol. 44(17):6532-6549. Phenrat, T., N. Saleh, K. Sirk, H.J. Kim, R.D. Tilton, and G.V. Lowry. 2008. Stabiliza- tion of aqueous nanoscale zerovalent iron dispersions by anionic polyelectrolytes: Adsorbed anionic polyelectrolyte layer properties and their effect on aggregation and sedimentation. J. Nanopart. Res. 10(5):795-814. Phenrat, T., T.C. Long, G.V. Lowry, and B. Veronesi. 2009. Partial oxidation ("aging") and surface modification decrease the toxicity of nanosized zerovalent iron. Environ. Sci. Technol. 43(1):195-200. Richman, E.K., and J.E. Hutchison. 2009. The nanomaterial characterization bottleneck. ACS Nano. 3(9):2441-2446. Saleh, N., H.J. Kim, T. Phenrat, K. Matyjaszewski, R.D. Tilton, and G.V. Lowry. 2008. Ionic strength and composition affect the mobility of surface-modified Fe0 nanoparticles in water-saturated sand columns. Environ. Sci. Technol. 42(9):3349- 3355. Schierz, P.A., A.N. Parks, and P.L. Ferguson. 2010. Characterization and Analysis of Single-walled Carbon Nanotubes in Complex Matrices by Asymmetric Flow FFF Coupled with NIRF Spectroscopy. Presentation at the 5th Annual Conference on Environmental Effects of Nanoparticles and Nanomaterials, August 2010, Clem- son, SC. Schmieder, P.K., G. Ankley, O. Mekenyan, J.D. Walker, and S. Bradbury. 2003. Quanti- tative structure-activity relationship models for prediction of estrogen receptor

142 Identifying Properties of Engineered Nanomaterials That Indicate Risks binding affinity of structurally diverse chemicals. Environ. Toxicol. Chem. 22(8):1844-1854. Smith, J.N., K.C. Barsanti, H.R. Friedli, M. Ehn, M. Kulmala, D.R. Collins, J.H. Scheckman, J. Williams, and P.H. McMurry. 2010. Observations of aminium salts in atmospheric nanoparticles and possible climatic implications. Proc. Natl. Acad. Sci. U.S.A. 107(15):6634-6639. Tan, W., R. Madduri, A. Nenadic, S. Soiland-Reyes, D. Sulakhe, I. Foster, and C. Goble. 2010. CaGrid Workflow Toolkit: A taverna based workflow tool for cancer grid. BMC Bionformatics 11:542. Teeguarden, J.G., P.M. Hinderliter, G. Orr, B.D. Thrall, and J.G. Pounds. 2007. Parti- cokinetics in vitro: Dosimetry considerations for in vitro nanoparticle toxicity as- sessments. Toxicol. Sci. 95(2):300-312. Thomas, D.G., R.V. Pappu, and N.A. Baker. 2011. NanoParticle Ontology for cancer nanotechnology research. J. Biomed. Inform. 44(1):59-74. Tiede, K., M. Hassellöv, E. Breitbarth, Q. Chaudhry, and A.B. Boxall. 2009. Considera- tions for environmental fate and ecotoxicity testing to support environmental risk assessments for engineered nanoparticles. J. Chromatogr. A. 1216(3):503-509. Vietti-Cook, A.L. 1999. Staff Requirements - SECY-98-144 - White Paper on Risk- Informed and Performance-Based Regulation. Memorandum to William D. Travers, Executive Director for Operations, from Annette L. Vietti-Cook, Secretary, U.S. Nu- clear Regulatory Commission. March 1, 1999 [online]. Available: http://pbadupws. nrc.gov/docs/ML0037/ML003753601.pdf [accessed Nov. 28, 2011]. von der Kammer, F., P.L. Ferguson, P.A. Holden, A. Masion, K.R. Rogers, S.J. Klaine, A.A. Koelmans, N. Horne, and J.M. Unrine. 2012. Analysis of engineered nano- materials in complex matrices (environment & biota): General considerations and conceptual case studies. Environ. Toxicol. Chem. 31(1):32-49. W3C Semantic Web. 2011. W3C Semantic Web Activity [online]. Available: http:// www.w3.org/2001/sw/ [accessed May 16, 2011]. Walczyk, D., F.B. Bombelli, M.P. Monopoli, I. Lynch, and K.A. Dawson. 2010. What the cell “sees” in bionanoscience. J. Am. Chem. Soc. 132(16):5761-5768. Wiesner, M.R., G.V. Lowry, P. Alvarez, D. Dionysiou, and P. Biswas. 2006. Assessing the risks of manufactured nanomaterials. Environ. Sci. Technol. 40(14):4336- 4345. Wiesner, M.R., G.V. Lowry, K.L. Jones, M.F. Hochella, Jr., R.T. Di Giulio, E. Casman, and E.S Bernhardt. 2009. Decreasing uncertainties in assessing environmental ex- posure, risk, and ecological implications of nanomaterials. Environ. Sci. Technol. 43(17):6458-6462. Zhao, J., F.L. Eisele, M. Titcombe, C.G. Kuang, and P.H. McMurry. 2010. Chemical ionization mass spectrometric measurements of atmospheric neutral clusters using the cluster-CIMS. J. Geophys. Res. 115:D08205.

Next: 5 Research Priorities and Resource Needs »
A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials Get This Book
×
Buy Paperback | $57.00 Buy Ebook | $45.99
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

The nanotechnology sector, which generated about $225 billion in product sales in 2009, is predicted to expand rapidly over the next decade with the development of new technologies that have new capabilities. The increasing production and use of engineered nanomaterials (ENMs) may lead to greater exposures of workers, consumers, and the environment, and the unique scale-specific and novel properties of the materials raise questions about their potential effects on human health and the environment. Over the last decade, government agencies, academic institutions, industry, and others have conducted many assessments of the environmental, health, and safety (EHS) aspects of nanotechnology. The results of those efforts have helped to direct research on the EHS aspects of ENMs. However, despite the progress in assessing research needs and despite the research that has been funded and conducted, developers, regulators, and consumers of nanotechnology-enabled products remain uncertain about the types and quantities of nanomaterials in commerce or in development, their possible applications, and their associated risks.

A Research Strategy for Environmental, Health, and Safety Aspects of Engineered Nanomaterials presents a strategic approach for developing the science and research infrastructure needed to address uncertainties regarding the potential EHS risks of ENMs. The report summarizes the current state of the science and high-priority data gaps on the potential EHS risks posed by ENMs and describes the fundamental tools and approaches needed to pursue an EHS risk research strategy. The report also presents a proposed research agenda, short-term and long-term research priorities, and estimates of needed resources and concludes by focusing on implementation of the research strategy and evaluation of its progress, elements that the committee considered integral to its charge.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!